Dionysis Athanasopoulos

CoWSAMI: Interface-aware context gathering in ambient intelligence environments

In this paper we present CoWSAMI, a middleware infrastructure that enables context awareness in open ambient intelligence environments, consisting of mobile users and context sources that become dynamically available as the users move from one location to another. A central requirement in such dynamic scenarios is to be able to integrate new context sources and users at run-time. CoWSAMI exploits a novel approach towards this goal. The proposed approach is based on utilizing Web services as interfaces to context sources and dynamically updatable relational views for storing, aggregating and interpreting context. Context rules are employed to provide mappings that specify how to populate context relations, with respect to the different context sources that become dynamically available. An underlying context sources discovery mechanism is utilized to maintain context information up to date as context sources, and users get dynamically involved.

Service Substitution Revisited

In this paper, we propose a framework that reduces the complexity of service substitution. The framework is based on two substitution relations and corresponding theorems. The proposed relations and theorems allow organizing available services into groups. Then, the complexity of retrieving candidate substitute services for the target service and generating corresponding adapters scales up with the number of available groups, instead of scaling up with the number of available services.

Fine-Grained Metrics of Cohesion Lack for Service Interfaces

A design issue that often appears in real-world services is that their interfaces are not cohesive, i.e., they consist of many and possibly unrelated operations. This issue may complicate the comprehension of the services functionalities and the maintenance of the applications that use them. Currently, the state of the art on case studies that focus on the evaluation of the cohesion of services offered by major service providers is limited, while research efforts on corresponding cohesion metrics are at a quite early stage. In particular, there exist coarse-grained metrics of cohesion lack, which consider that the operations of a service interface are related if the types of certain of their input/output data exactly match. The problem in this approach is that operations which operate on data characterized by similar, but not exactly matching, types are treated as being totally unrelated. Consequently, the aforementioned metrics may overestimate the cohesion lack of service interfaces. In this paper, we undertake a more elaborate approach to evaluate a set of real world services provided by Amazon. Specifically, we propose two fine-grained metrics of cohesion lack, which are defined with respect to the structural similarity of the input/output data types of interface operations. The proposed metrics are formally defined and analytically assessed with respect to fundamental properties of software metrics. Finally we report the results from our case study.

Mining service abstractions (NIER track)

Several lines of research rely on the concept of service abstractions to enable the organization, the composition and the adaptation of services. However, what is still missing, is a systematic approach for extracting service abstractions out of the vast amount of services that are available all over the Web. To deal with this issue, we propose an approach for mining service abstractions, based on an agglomerative clustering algorithm. Our experimental findings suggest that the approach is promising and can serve as a basis for future research.

Cohesion-Driven Decomposition of Service Interfaces without Access to Source Code

Software cohesion concerns the degree to which the elements of a module belong together. Cohesive software is easier to understand, test and maintain. In the context of service-oriented development, cohesion refers to the degree to which the operations of a service interface belong together. In the state of the art, software cohesion is improved based on refactoring methods that rely on information, extracted from the software implementation. This is a main limitation towards using these methods in the case of web services: web services do not expose their implementation; instead all that they export is the web service interface specification. To deal with this problem, we propose an approach that enables the cohesion-driven decomposition of service interfaces, without information on how the services are implemented. Our approach progressively decomposes a given service interface into more cohesive interfaces; the backbone of the approach is a suite of cohesion metrics that rely on information, extracted solely from the specification of the service interface. We validate the approach in 22 real-world services, provided by Amazon and Yahoo. We assess the effectiveness of the proposed approach, concerning the cohesion improvement, and the number of interfaces that result from the decomposition of the examined interfaces. Moreover, we show the usefulness of the approach in a user study, where developers assessed the quality of the produced interfaces.

Service selection for happy users: making user-intuitive quality abstractions

The state of the art service search engines allow the users to pick the services they need, based on the quality properties, offered by these services. To this end, the users should interact with the search engines based on the quality models that are imposed by the engines. This is a significant restriction towards making the service-oriented paradigm attractive to the general public. In this paper, we propose an approach that allows a user to specify his perception of quality in terms of a simple, user-defined quality model. The proposed approach automatically maps the user-defined quality model to the search engines quality model. This mapping forms the basis for ordering, grouping and, in general manipulating, the results of the users service discovery requests.

The Aspect of Data Translation in Service Similarity

To avoid the lock-in problem in service-oriented software, existing interface-decoupling mechanisms focus on identifying high-level service mappings, which are not necessarily applicable on translating actual data. Based on the fundamental data-translation process, its successful outcome is guaranteed if mappings are low-level, i.e. they satisfy schema constraints. The problem is that if similar services have been identified based on high-level mappings, then schema constraints may be violated. To overcome this problem, we propose a proactive approach to identify similar services that satisfy schema constraints. In particular, our approach follows a composite workflow (instead of existing hybrid workflows), which determines schema constraints (service documents do not specify them) and estimates service-translation cost (actual cost is not available) as a function of ensured schema-constraints. We compare our approach against a state-of-the-art service-similarity approach on benchmark services and the results show that high service-similarity does not necessarily imply low service-translation cost, the bidirectional nature of service similarity can be misleading, ensured schema-constraints improve service similarity, and estimated translation-cost is very close to actual cost.

Multi-objective Service Similarity Metrics for More Effective Service Engineering Methods (Short Paper)

The usage of single-objective similarity functions in engineering tasks of service-oriented software may reduce their effectiveness, since a single similarity value can be misleading. In particular, a single similarity value cannot be clearly interpreted, since it hides the values of its individual objectives. The state-of-the-art approaches, which use service similarity functions, typically rely on single-objective functions. Going in a complementary direction, we propose the usage of multi-objective functions for calculating service similarity. We formally define such a function and we provide emerging results, which show that the effectiveness of service engineering tasks can be improved by using multi-objective functions.